Study design and study population
Details on the design of the NordICC trial have been reported elsewhere [4]. Briefly, this trial was run in four Northern European countries, Poland, Norway, Sweden and the Netherlands, but data from the Netherlands were not included for legal reasons in the first report on long-term effect estimates, published in October 2022. The study population for that analysis, which was drawn from population registries, included 84,585 presumptively healthy men and women 55-64 years of age who were randomized in a 1:2 ratio to either receive an invitation for a single colonoscopy or to usual-care between 2009 and 2014. Out of 28,220 participants in the invited group, 11,843 (42.0%) followed the invitation. Primary endpoints were risk of total CRC incidence and death. Follow-up was performed by record linkage with cancer registries and cause-of-death registries. During a median follow-up of 10 years, 259 and 622 CRC cases were registered in the invited group and the usual-care group, respectively. Among the 259 CRC cases in the invited group, 102 were registered among attenders of screening colonoscopy, of which 62 were prevalent, screening-detected cases and 40 were truly incident cases (Table 1, upper part). The numbers of prevalent and incident cases could not be directly determined for non-attenders of screening and for participants in the usual-care group who did not receive an intervention.
Statistical analysis
The aim of this statistical analysis was to derive estimates of relative risk of truly incident CRC even though these cases could not be directly observed among non-attenders of screening and for participants in the usual-care group. Just excluding known prevalent CRC cases among screening attenders from the outcome measures would not be an option because selective exclusion of such cases for screening attenders would lead to overestimation of screening effects. Thus, it is necessary to also estimate the numbers of both prevalent and incident CRC cases among non-attenders of screening and participants in the usual-care group and then carry out an additional analysis after excluding prevalent cases from event numbers for all groups of participants.
The assumptions made in our analysis are listed in Table 2. The first assumption is that equal proportions of prevalent and incident cases in the invited group and the usual-care group would be expected if screening did not have any effect. This assumption should be ensured by the randomized study design and the very large number of study participants in each group. The second assumption, which is required for intention-to-screen analyses of reduction of incident cases only, expects equal shares of prevalent CRC cases among all CRC cases among non-attenders and attenders of screening in the absence of screening effects, which also appears plausible. Note that this assumption does not require equal CRC risks among attenders and non-attenders of screening. Furthermore, we conducted sensitivity analyses to evaluate the potential impact of even major violation of this assumption.
Step 1: Calculate the expected number of CRC cases prevented by screening:
From the published data, we first derived the total number of CRC cases that would have been expected in the invited group if screening did not have any preventive effect. This number was derived by multiplying the number of participants in the invited group with the apparent cumulative incidence in the usual-care-group: 28,220 x (622/56,365) = 311. As only 259 such cases were observed in the invited group this suggests that 311-259=52 CRC cases have been prevented by screening (Table 1, middle part).
Step 2: Calculate the number of incident cases that would have been expected in the screened group, if this group had not been screened:
The prevented cases would be expected to otherwise have occurred as incident cases among screening attenders, which would have resulted in 40+52=92 incident CRC cases. Together with 62 prevalent (screening-detected) CRC cases, 92+62=154 total CRC cases would have been expected in the screening attenders in the absence of screening effects (Table 1, middle part).
Step 3: Calculate the expected number of prevalent and incident cases in screening non-attenders and in the usual care group:
Assuming the same shares of prevalent and incident cancers among all cancers in screening non-attenders and attenders if screening had no effect, i.e. 62/154=0.40 and 92/154=0.60, respectively, the expected numbers of prevalent and incident CRC cases can be derived as 157×0.40=63 and 157×0.60=94 in screening-non-attenders and as 622×0.40=250 and 622×0.60=372 in the usual-care group (Table 1, middle part).
Step 4: For the screened group, use the actually observed values for prevalent and incident cases:
From the so-derived expected numbers of prevalent and incident CRC cases in the absence of screening effects we derived the corresponding numbers with screening effects by replacing the respective numbers in screening attenders by the observed, lower numbers. The numbers of total and incident CRC cases in the total invited group were reduced accordingly (Table 1, lower part).
Calculation of relative risks
We derived estimates of relative risks of both total (prevalent and incident) CRC and of incident CRC according to both intention-to-screen and per-protocol analysis. Intention-to-screen estimates, which quantify the impact of the screening offer on the CRC risk, were derived as ratios of case numbers with and without screening in the invited group. Adjusted per-protocol estimates, which quantify the impact of actual use of screening on the CRC risk, were derived as ratios of case numbers with and without screening in the screened group.
This approach of deriving adjusted per-protocol estimates is unaffected by potential differences in baseline risk between screening attenders and non-attenders and corresponds to such adjustment according to the method proposed by Cuzick et al. [13] used in sensitivity analyses of the original NordICC trial report. We derived 95% confidence intervals for our relative risk estimates as the 2.5th and 97.5th percentile of one million runs of Monte Carlo simulations of the NordICC trial, using the observed case proportions as expected values for each simulation run. A more general formal description of the derivation of relative risks is provided in the Supplementary Material 1, and the R code used for the Monte Carlo simulations is provided in the Supplementary Material 2.
Besides enabling separate estimates of screening effects for incident (potentially preventable) CRC cases, our approach slightly differs from the original analysis of the NordICC trial in that relative risk estimates were based on count data rather than incidence rate (person-time) data. In order to judge the relevance of this slight difference, we present the relative risk estimates for total CRC (prevalent and incident CRC combined) from the original publication side-by-side with our estimates.